MultiCare Health System pilots new AI tool for revenue cycle
GenAI is expected to streamline documentation for appeals, providing faster reimbursement.
Photo: Andrey Popov/Getty Images
MultiCare Health System in Washington State is the first health system to pilot a new generative AI tool to streamline appeals in the mid-revenue cycle, according to AI technology company Xsolis.
The technology is used to create and submit appeal letters, saving administrative time and ensuring health plan appeal deadlines are met.
WHY THIS MATTERS
The bottom line is hospitals are reimbursed faster, Xsolis said.
Streamlining documentation in the revenue cycle eases clinical burden and saves money.
MultiCare Health System has partnered with Xsolis' AI platform for operational and clinical efficiencies since 2017, increasing case review times by 150% and saving more than $8 million, Xsolis said.
THE LARGER TREND
MultiCare began working with Xsolis in 2017 and is the first health system to pilot Xsolis' generative AI tool.
A recent Harris Poll estimates clinicians spend around 28 hours a week on administrative tasks – including almost nine hours a week on documentation, the company said.
Xsolis, headquartered in Franklin, Tennessee, said its new generative AI solution and its existing predictive AI models have saved health systems and health plans more than $1.5 billion.
MultiCare Health System, based in Tacoma, Washington, is a not-for-profit healthcare organization with 13 hospitals.
ON THE RECORD
"Through our continued partnership with Xsolis, we've reduced administrative tasks, improved payer relations, and established a successful track record of operational and financial improvements," said Debbie Schardt, assistant vice president of revenue cycle and utilization management with MultiCare Health System. "Xsolis' enhanced generative AI capabilities will build on our successes in critical areas, including, reducing burnout, improving job satisfaction, and generating financial savings for the organization."
Email the writer: SMorse@himss.org